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167
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2007
136views Robotics» more  RSS 2007»
15 years 5 months ago
The Stochastic Motion Roadmap: A Sampling Framework for Planning with Markov Motion Uncertainty
— We present a new motion planning framework that explicitly considers uncertainty in robot motion to maximize the probability of avoiding collisions and successfully reaching a ...
Ron Alterovitz, Thierry Siméon, Kenneth Y. ...
154
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AAAI
2006
15 years 5 months ago
Decision Making in Uncertain Real-World Domains Using DT-Golog
DTGolog, a decision-theoretic agent programming language based on the situation calculus, was proposed to ease some of the computational difficulties associated with Markov Decisi...
Mikhail Soutchanski, Huy Pham, John Mylopoulos
180
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APBC
2004
132views Bioinformatics» more  APBC 2004»
15 years 5 months ago
A Novel Feature Selection Method to Improve Classification of Gene Expression Data
This paper introduces a novel method for minimum number of gene (feature) selection for a classification problem based on gene expression data with an objective function to maximi...
Liang Goh, Qun Song, Nikola K. Kasabov
ACL
2006
15 years 5 months ago
Minimum Risk Annealing for Training Log-Linear Models
When training the parameters for a natural language system, one would prefer to minimize 1-best loss (error) on an evaluation set. Since the error surface for many natural languag...
David A. Smith, Jason Eisner
137
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CSREASAM
2006
15 years 5 months ago
Session Based Logging (SBL) for IP-Traceback on Network Forensics
The widely acknowledged problem of reliably identifying the origin of information in cyberspace has been the subject of much research. Due to the nature of the Internet protocol, ...
Omer Demir, Ping Ji, Jinwoo Kim
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